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Assessing two methods for estimating excess mortality of chronic diseases from aggregated data
Ralph Brinks1,2, Thaddäus Tönnies3, Annika Hoyer3
1Institute for Biometry and Epidemiology, German Diabetes Center, Auf'm Hennekamp 65, 40225, Duesseldorf, Germany. ralph.brinks@ddz.de.
BMC Research Notes
|April 18, 2020
Summary
Two new methods for estimating excess mortality from diabetes data in Germany produced questionable results. The techniques yielded implausible figures for type 2 diabetes deaths in individuals under 50.
Area of Science:
- Epidemiology
- Biostatistics
Background:
- Excess mortality estimation is crucial for public health.
- Diabetes poses a significant mortality burden.
- Recent advancements in statistical methods aim to improve estimation accuracy.
Purpose of the Study:
- To evaluate the numerical performance of two novel estimation techniques.
- To assess the validity of these methods using German diabetes claims data.
Main Methods:
- Application of two recently published estimation techniques.
- Analysis of aggregated diabetes data from German health claims.
- Evaluation of numerical properties and plausibility of results.
Main Results:
- The new methods generated implausible excess mortality estimates.
- Specifically, results for type 2 diabetes in individuals under 50 years were unrealistic.
- The numerical properties of the techniques require further scrutiny.
Conclusions:
- The assessed estimation techniques may not be suitable for all populations or age groups.
- Further validation and refinement of excess mortality estimation methods are needed.
- Caution is advised when interpreting results for specific subgroups, particularly younger populations.
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